Computational Infrastructure Research Articles

Efficient Resource Utilization in IoT and Cloud Computing

With the proliferation of IoT devices, there has been exponential growth in data generation, placing substantial demands on both cloud computing (CC) and internet infrastructure. CC, renowned for its scalability and virtual resource provisioning, is of paramount importance in e-commerce applications. However, the dynamic nature of IoT and cloud services introduces unique challenges, notably in the establishment of service-level agreements (SLAs) and the continuous monitoring of compliance. This paper presents a versatile framework for the adaptation of e-commerce applications to IoT and CC environments. It introduces a comprehensive set of metrics designed to support SLAs by enabling periodic resource assessments, ensuring alignment with service-level objectives (SLOs). This policy-driven approach seeks to automate resource management in the era of CC, thereby reducing the dependency on extensive human intervention in e-commerce applications. This paper culminates with a case study that demonstrates the practical utilization of metrics and policies in the management of cloud resources. Furthermore, it provides valuable insights into the resource requisites for deploying e-commerce applications within the realms of the IoT and CC. This holistic approach holds the potential to streamline the monitoring and administration of CC services, ultimately enhancing their efficiency and reliability.

Improved End-to-End Data Security Approach for Cloud Computing

Cloud computing is one of the major cutting-edge technologies that is growing at a gigantic rate to redefine computation through service-oriented computing. It has addressed the issue of owning and managing computational infrastructure by providing service through a pay-and-use model. However, a major possible hindrance is security breaches, especially when the sender uploads or the receiver downloads the data from a remotely accessed server. It is a very generic approach to ensuring data security through different encryption techniques, but it might not be able to maintain the security standard. This paper proposes an end-to-end data security approach from the sender side to the receiver side by adding extra padding sequences, as well as randomized salting, followed by hashing and an encryption technique. The effectiveness of the proposed method was established using both a simulated system and mathematical formulations with different performance metrics. Furthermore, its performance was compared with those of contemporary algorithms, showing that the proposed algorithm creates a larger ciphertext that is almost impossible to crack due to randomization modules. However, it has significantly longer encryption and decryption times, although our primary concern is ensuring security, not reducing time.

RegulonDB v12.0: a comprehensive resource of transcriptional regulation in E. coli K-12.

RegulonDB is a database that contains the most comprehensive corpus of knowledge of the regulation of transcription initiation of Escherichia coli K-12, including data from both classical molecular biology and high-throughput methodologies. Here, we describe biological advances since our last NAR paper of 2019. We explain the changes to satisfy FAIR requirements. We also present a full reconstruction of the RegulonDB computational infrastructure, which has significantly improved data storage, retrievaland accessibility and thus supports a more intuitive and user-friendly experience. The integration of graphical tools provides clear visual representations of genetic regulation data, facilitating data interpretation and knowledge integration. RegulonDB version 12.0can be accessed at https://regulondb.ccg.unam.mx.

Risk Factors for Penile Fracture After Intralesional Collagenase Clostridium histolyticum in Peyronie’s Disease

ObjectivesTo evaluate risk factors leading to corporal rupture after Collagenase Clostridium histolyticum (CCh). Peyronie's disease (PD) is a fibrotic condition of the penis characterized by abnormal plaque formation. Intralesional CCh is the only FDA approved medication for PD, however it can lead to corporal rupture, a potential surgical emergency. MethodsWe retrospectively reviewed medical records from Veterans diagnosed with PD who were under treatment with CCh using the Veterans Administration Informatics and Computing Infrastructure (VINCI). Using International Classification of Diseases and Current Procedural Terminology codes, we identified men who suffered a corporal rupture after CCh. Individual charts were reviewed to determine potential risk factors and events leading to corporal rupture. ResultsWe identified 17,647 veterans who were diagnosed with PD, of which 8.7% (1,541) received at least one injection of CCh for PD. Of them, 0.7% (11/1,541) veterans suffered corporal rupture. Within these 11 patients, the median number of CCH injections was 6 with a median initial curvature of 35º. Fracture occurred at a median of 8 days after CCH injection. The majority of fractures were secondary to spontaneous erections or sexual intercourse. Finally, six patients had their fracture repaired surgically while the remaining were managed conservatively. ConclusionsMost fractures occurred within 2 weeks of CCh injections and were associated with sexual intercourse and spontaneous morning erections.

Abstract 13028: Estimating Cardiovascular Event Rates in US Veterans Using the SMART Risk Score

Background: There is limited data on racial differences in long term cardiovascular (CV) outcomes amongst U.S. veterans. Methods: Utilizing the VA Informatics and Computing Infrastructure and the Corporate Data Warehouse we compared 10-year predicted major adverse CV events [MACE, a composite of all-cause death and non-fatal myocardial infarction] in patients referred for cardiovascular consultation between 2003 and 2009 using the SMART risk score with observed rates across racial groups. The SMART risk score classified patients into low 0-9.9%, intermediate 10-19.9%, high 20-29.9%, and very high >=30% risk groups. Results: 473,136 patients including white (74.7%), African American (15.5%), and other (9.8%) made the study cohort. Observed event rates were significantly higher in African Americans compared with Whites across all SMART risk groups [p<0.001], and highest in the other races, inclusive of Hispanics. These results are depicted in Figure 1 . Conclusion: There is a significantly higher observed 10-year MACE rate in African American veterans compared with their white counterparts across all predicted SMART risk score groups.

Characteristics and Outcomes of Lymphoid Malignancies in Veterans Exposed to Burn Pits

Introduction Military personnel were deployed to the Middle East for the Persian Gulf War (8/1990-7/1991), Operation Enduring Freedom (10/2001-12/2014), and Operation Iraqi Freedom (3/2003-11/2011), where they were exposed to environmental hazards including geological dust chemical smoke from burn pits, and heavy metal condensates 1. Burn pits are open-air fires that are used to dispose of food, human waste, plastic bottles, and electronic equipment during the conflicts in the Middle East and release high levels of dioxins, furans, particulate matter, polycyclic aromatic hydrocarbons, and volatile organic compounds, all well established as known human carcinogens 1. Outcomes in veterans diagnosed with lymphoid malignancies with and without burn pit exposure are unknown and warrant further study. Methods This is a retrospective case-case analysis of veterans diagnosed with mature lymphoid malignancies identified from the VA Cancer Registry 2. Descriptive statistics were used to compare cases with and without burn pit risk. Burn pit risk was defined as exposure to Iraq or Afghanistan from the VA Cancer Registry, combat in the Middle East from the VA disability database, or exposure to known chemical locations at Al Jubayl in Saudi Arabia or Khamisiyah in Iraq from USVETS. The Persian Gulf War began 8/2/90 and was considered the presumptive start date of burn pit risk, which was calculated from time at risk until exit from the military. Latency was defined as the time from exposure to the development of a lymphoid malignancy. Cases were excluded if veterans exited the military before 8/2/90 or entered after 12/31/14, latency of exposure to the diagnosis of lymphoid malignancy <6 months, or the burn pit risk was <1 month from 8/2/90 to exit from military. Overall survival (OS) was calculated by time from diagnosis to date of death or last contact, and disease specific survival (DSS) was calculated from time from diagnosis to date of death from a hematologic malignancy or last contact. OS and DSS by histologic subtype were compared by the Kaplan Meier method. Dates and causes of death were determined by the National Death Index, which provided data up to 12/31/20 (data cut off date) 3. Results Patient characteristics are summarized in Table 1. Veterans exposed to burn pits were diagnosed with a lymphoid malignancy at a younger age compared to the unexposed group (47 vs 52 years, p<0.0001). There were differences in racial distribution between the two groups (p=0.0463). More veterans who were exposed to burn pits enlisted in the army (56.8% vs 37.3%) and fewer in the navy (10.2% vs 21.0%) compared to the unexposed group (p<0.0001). Exposed patients had a higher frequency of Hodgkin lymphoma (17.5% vs 12.7%) and lower frequency of plasma cell neoplasms (17.8% vs 20.6%) and chronic lymphocytic leukemia (14.4% vs 16.2%) compared to those who were unexposed (p=0.0002). The difference in age between the exposed and unexposed group may contribute to the different frequencies of these subtypes. By histologic subtypes, the median OS and DSS were not significantly different between the two groups. More patients in the unexposed group died when compared to the exposed group (25.2% vs 18.9%, p<0.0001), but the causes of death did not differ. Conclusion Veterans exposed to burn pits may be diagnosed with a lymphoid malignancy at a younger age compared to unexposed veterans, but there is no difference in median OS or DSS by histologic subtype. More veterans who were unexposed to burn pits died but there were no differences in the causes of death between the two groups. This may be explained by the exposed group being younger and the “healthy soldier effect”. We are continuing to examine the effect of burn pits on the development and outcomes of lymphoid malignancies in more detail. Citations 1 Institute of Medicine. Long-Term Health Consequences of Exposure to Burn Pits in Iraq and Afghanistan. Washington, DC: The National Academies Press; 2011. 2 US Department of Veteran Affairs. VA Informatics and Computing Infrastructure (VINCI), VA ORD 22-D4V, U.S. Department of Veterans Affairs. 2008. Retrieved August 1, 2022, from https://vincicentral.vinci.med.va.gov. 3 Veterans Health Administration Center of Excellence for Suicide Prevention. Joint Department of Veterans Affairs and Department of Defense Mortality Data Repository. 2022. Data compiled from the National Death Index. Extract December 6, 2022.

Clinical Characteristics and Outcomes of Unusual Venous Thrombosis Sites Among Veterans with Myeloproliferative Neoplasms

Myeloproliferative Neoplasms (MPNs) may be complicated by venous thrombosis at unusual sites, which may include portal veins, hepatic veins, and cerebral sinuses. We have previously reported on the association of Agent Orange and the development of MPNs among Veterans. The incidence and timing from Service-Connected Exposures (SCE) of Veterans to the development of MPNs and thrombosis at atypical sites have not been defined. We examine the natural history, clinical characteristics, and outcomes of the Veterans with MPNs, who developed Renal Vein Thrombosis (RVT), Splanchnic Vein Thrombosis (SVT), Budd Chiari Syndrome (BCS), and Cerebral Venous Sinus Thrombosis (CVST). Utilizing the Veterans Affairs Informatics and Computing Infrastructure (VINCI) database from January 1, 2006 - January 26, 2023, Veterans with MPNs, RVT, SVT, BCS, and CVST were identified through ICD-9 and -10 codes, and, subsequently, a retrospective chart review was performed upon those Veterans with MPNs and unusual thrombosis sites. Military toxin exposures were verified through Veterans' duration and location of service. Time to MPN diagnosis refers to time from first year of cumulative SCE until year of MPN diagnosis. Among 12,352,664 Veterans, there were 435 RVT, 156 SVT and BCS, 140 CVST, and 93,269 MPNs identified. Among those with MPNs, there were 9 BCS, 4 RVT, 5 SVT, 2 RVT & SVT, and 9 CVST. CVST was observed only in Vietnam Veterans; 13/20 (65%) of RVT, SVT or BCS cases had SCE from the Gulf War (Table 1). Five/20 of the MPN subjects with RVT, SVT, or BCS had documented pre-existing thrombophilic risk factors, which included malignancy, heparin-induced thrombocytopenia, and splenectomy, whereas 2/9 CVST with MPN had associated alcohol abuse and tooth infection. All non-MPN Veterans with RVT, SVT, or BCS had thrombophilic risk factors, including malignancy, infection, and surgery. One had BCS from Paroxysmal Nocturnal Hemoglobinuria. Median time to MPN diagnosis from SCE was 20 (3-62) years with 13 (65%) thrombotic events occurring at the same time of MPN diagnosis among Veterans with RVT, SVT, or BCS. Six (30%) had their thrombosis recognized prior to their MPN diagnosis, median 6 (1-10) years, while 1 had a thrombotic event 16 years after his MPN diagnosis (Figure 1). Veterans with MPN and CVST had a substantially longer median time from SCE to the time of MPN diagnosis, 42 (24-52) years. No CVST was observed concurrent to the time of MPN diagnosis. Among Veterans with MPN and CVST, 5 (56%) had thrombosis before MPN diagnosis and 4 (44%) had thrombosis after MPN diagnosis, median 5 (2-10) years and 7 (1-21) years, respectively. Among Veterans with MPN and RVT, SVT, or BCS, 17 (85%) had portal hypertension complications, 8 (40%) had undergone endovascular interventions, and all individuals were placed on indefinite systemic anticoagulation, with warfarin most commonly prescribed. Among Veterans with BCS, 3 underwent liver transplantation. Among Veterans with CVST, 2 (22%) had concurrent CNS hemorrhage, 5 (56%) had persistent neurologic symptoms, and 1 had transformation of his MPN to Chronic Myelomonocytic Leukemia. In summary, thrombotic episodes at unusual sites among Veterans with MPNs are rare events but convey substantial morbidity and mortality, particularly among those with RVT, SVT, and BCS. We describe a significantly shorter median time to MPN diagnosis in Veterans with RVT, SVT, and BCS compared to CVST with a difference of 22 years. All MPN subjects with RVT, SVT, or BCS had JAK2 V617F mutations, with majority of thromboses noted at the time of MPN diagnosis. Future studies should include potential role of SCE in acquisition of driver mutations and CHIPs and progression of mutagenesis.

Engineering the future of 3D pathology.

In recent years, technological advances in tissue preparation, high-throughput volumetric microscopy, and computational infrastructure have enabled rapid developments in nondestructive 3D pathology, in which high-resolution histologic datasets are obtained from thick tissue specimens, such as whole biopsies, without the need for physical sectioning onto glass slides. While 3D pathology generates massive datasets that are attractive for automated computational analysis, there is also a desire to use 3D pathology to improve the visual assessment of tissue histology. In this perspective, we discuss and provide examples of potential advantages of 3D pathology for the visual assessment of clinical specimens and the challenges of dealing with large 3D datasets (of individual or multiple specimens) that pathologists have not been trained to interpret. We discuss the need for artificial intelligence triaging algorithms and explainable analysis methods to assist pathologists or other domain experts in the interpretation of these novel, often complex, large datasets.

Novel Computational Chemistry Infrastructure for Simulating Astatide in Water: From Basis Sets to Force Fields Using Particle Swarm Optimization.

Using the example of astatine, the heaviest naturally occurring halogen whose isotope At-211 has promising medical applications, we propose a new infrastructure for large-scale computational models of heavy elements with strong relativistic effects. In particular, we focus on developing an accurate force field for At- in water based on reliable relativistic density functional theory (DFT) calculations. To ensure the reliability of such calculations, we design novel basis sets for relativistic DFT, via the particle swarm optimization algorithm to optimize the coefficients of the new basis sets and the polarization-consistent basis set idea's extension to heavy elements to eliminate the basis set error from DFT calculations. The resulting basis sets enable the well-grounded evaluation of relativistic DFT against "gold-standard" CCSD(T) results. Accounting for strong relativistic effects, including spin-orbit interaction, via our redesigned infrastructure, we elucidate a noticeable dissimilarity between At- and I- in halide-water force field parameters, radial distribution functions, diffusion coefficients, and hydration energies. This work establishes the framework for the systematic development of polarization-consistent basis sets for relativistic DFT and accurate force fields for molecular dynamics simulations to be used in large-scale models of complex molecular systems with elements from the bottom of the periodic table, including actinides and even superheavy elements.

MULTI-CRITERIA SELECTION OF STANDARDS FOR SYSTEM ANALYST ACTIVITIES IN ORGANIZATIONS

The paper defines the methodology for the selection of standards and tools that system analysts use for the purposes of analyzing the computer infrastructure of organizations. The goal of system analyst analysis is primarily to increase: the speed of processing information, the efficiency of data processing and data exchange. A large number of standards and tools complicates an adequate choice, and on the other hand system analysts are not the only ones who influence the choice. In the analysis of the choice of standards and tools, in the second chapter an algorithm for determining the weight coefficients for the criteria selected by the company and the ranking of the standards for selection is presented through an example. In order to choose the best standard, the choice was made between four standards described in the third chapter. The chapter defines the criteria that cover IT activities for the selection of standards according to selected criteria and defined weight coefficients in the observed company. Finally, on the assumption that the company together with the analyst chose “k” criteria, where the methodology (LBWA) for the selection of weight coefficients for the criteria was proposed, a new model for calculating the ranking of standards was presented, i.e. the choice of the best. The conclusion of the paper is that the presented procedure for choosing standards is not complicated, that it is very successful, and that in this way the proposals were more easily accepted and implemented in the fastest way.

Importance and Various Types of Task Scheduling in Cloud Computing System

Cloud Computing has arisen as quite possibly the main new computing procedures in the undertaking. A blend of advances and cycles has prompted an insurgency in the manner that computing is created and conveyed to end client. Cloud Computing traces all the way back to 1950 for example the enormous scope centralized servers were made accessible to huge undertakings. Basically, the cloud architecture is built with the combined perspective of cloud provider, user, and the broker. Scheduling is the most important task in any working framework, and it is controlled by the CPU. This is due to the fact that resources are not stored in a particularly designated manner, but rather in a strictly handy manner in order to ensure maximum skills. Cloud computing is a relatively new technology that allows users to access computer infrastructure and other services on a demand basis. Various types of task schedulers have been developed to make use of the vast amount of cloud-based resources users can access while also improving the management of data centers. We can say that cloud computing has transformed IT by allowing users and consumers to access services via the Internet. These services range from hardware to software, saving money on both the expense of setting up physical resources and the cost of obtaining the appropriate software licenses. The task scheduling problem is one of the most important and prominent challenges facing the cloud computing system.

Risk of Pancreatitis With Incretin Therapies Versus Thiazolidinediones in the Veterans Health Administration.

Incretin therapies, comprised of the dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs), have been increasingly utilized for the treatment of type 2 diabetes (T2DM). Previous studies have conflicting results regarding risk of pancreatitis associated with these agents-some suggest an increased risk and others find no correlation. Adverse event reporting systems indicate that incretin therapies are some of the most common drugs associated with reports of pancreatitis. This study aimed to compare the odds of developing pancreatitis in veterans with T2DM prescribed an incretin therapy versus thiazolidinediones (TZDs: pioglitazone and rosiglitazone) within the Veterans Health Administration (VHA). This was a retrospective cohort study analyzing veterans with T2DM first prescribed an incretin therapy or a TZD between January 1, 2011, and December 31, 2021. A diagnosis of pancreatitis within 365 days of being prescribed either therapy was counted as a positive case. Data was collected and analyzed utilizing VA's Informatics and Computing Infrastructure (VINCI) and an adjusted odds ratio was calculated. The TZD cohort consisted of 42 912 patients compared with the incretin cohort of 304 811 patients. The TZD cohort had a pancreatitis incidence rate of 1.94 cases per 1000 patients. The incretin cohort had a incidence rate of 2.06 cases per 1000 patients. An adjusted odds ratio found no statistical difference of pancreatitis cases between the TZD and incretin cohorts (adjusted odds ratio [AOR] = 0.94, 95% CI [0.75, 1.18]). This retrospective cohort study of national VHA data found a relatively low incidence of pancreatitis in both cohorts, and an adjusted odds ratio found no statistical difference of pancreatitis in patients prescribed an incretin therapy compared with a control group. This data adds to growing evidence that incretin therapies do not seem to be associated with an increased risk of developing pancreatitis.

Health data governance for research use in Alberta.

Alberta has rich clinical and health services data held under the custodianship of Alberta Health and Alberta Health Services (AHS), which is not only used for clinical and administrative purposes but also disease surveillance and epidemiological research. Alberta is the largest province in Canada with a single payer centralised health system, AHS, and a consolidated data and analytics team supporting researchers across the province. This paper describes Alberta's data custodians, data governance mechanisms, and streamlined processes followed for research data access. AHS has created a centralised data repository from multiple sources, including practitioner claims data, hospital discharge data, and medications dispensed, available for research use through the provincial Data and Research Services (DRS) team. The DRS team is integrated within AHS to support researchers across the province with their data extraction and linkage requests. Furthermore, streamlined processes have been established, including: 1) ethics approval from a research ethics board, 2) any necessary operational approvals from AHS, and 3) a tripartite legal agreement dictating terms and conditions for data use, disclosure, and retention. This allows researchers to gain timely access to data. To meet the evolving and ever-expanding big-data needs, the University of Calgary, in partnership with AHS, has built high-performance computing (HPC) infrastructure to facilitate storage and processing of large datasets. When releasing data to researchers, the analytics team ensures that Alberta's Health Information Act's guiding principles are followed. The principal investigator also ensures data retention and disposition are according to the plan specified in ethics and per the terms set out by funding agencies. Even though there are disparities and variations in the data protection laws across the different provinces in Canada, the streamlined processes for research data access in Alberta are highly efficient.

Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance.

The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or "California COVIDNet". This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.

The Markov Concept of the Energy Efficiency Assessment of the Edge Computing Infrastructure Peripheral Server Functioning over Time

The article is devoted to the research of the peripheral server energy consumption managing process defined based on the threshold policy by manipulating the values of the characteristic parameters of the arithmetic-logical complex of the latter. The research object is formalized by a Markov queue model with a single-threshold control scheme for the intensity of accepted requests service. A characteristic feature of the life cycle of a peripheral server is the non-stationary mode of operation in terms of energy consumption, due to the need to periodically poll the controlled sensor network and process the received data in real-time. To take into account this circumstance, the intensities of transitions in the heterogeneous birth-and-death Markov process of the created model are interpreted as non-random periodic functions of time. The resulting mathematical apparatus is summarized in the metric that allows us to estimate the target peripheral server’s energy consumption both at a specific moment and for a censored time interval (this distinguishes the obtained result from existing analogs).

Aerial computing: Enhancing mobile cloud computing with unmanned aerial vehicles as data bridges—A Markov chain based dependability quantification

Aerial Computing, utilizing unmanned aerial vehicles (UAVs), has emerged as a promising solution to enhance mobile cloud computing (MCC) infrastructure for the Internet of Things (IoT). The continuous generation of vast amounts of data by IoT devices requires efficient processing and monitoring for timely decision-making. However, wireless connections between IoT devices and remote servers can be unreliable, resulting in data loss. UAVs, with their increasing processing power and autonomy, can act as bridges between IoT devices and remote servers such as edge or cloud computing. In that context, this paper proposes a continuous time Markov chain (CTMC) models for an aerial computing system to evaluate system dependability metrics including availability and reliability. Sensitivity analysis is conducted to provide extended CTMC models with improved system availability. The proposed advanced model reduces downtime by 62 h compared to the baseline model, showcasing the potential of UAVs in enhancing the availability and reliability of MCC infrastructures. The use of UAVs and MCC in aerial computing is believed to be a win–win solution for cost-effective and energy-saving communication and computation services in various environments.

Future of Food Computing: Deepening the Scope by Broadening the Network

In recent years, there has been a growing interest in using food data in various areas of computer science. Food, as a fundamental necessity for human sustenance, undergoes complex processes from farm to fork, involving physical, biological, intellectual and emotional dimensions. The need to ensure the effective and sustainable functioning of global food systems, while addressing human and environmental challenges, necessitates the development of food computing. But the question remains: How should food computing evolve to address fundamental issues in the food systems? While global sharing of data, information andknowledge is a way forward, we propose to increase the effectiveness of this sharing by transcending narrow disciplinary boundaries and engaging a wider range of stakeholders to address practical challengesfacing human society. We argue that food computing requires a multidisciplinary approach that is expansive in both scope and effectiveness. We envision a future where food computing serves as a comprehensive computational infrastructure for all aspects of food, including its production, consumption, and impact on individuals and the environment. The field of Food Computing is highly relevant to Digital Humanities (DH) researchers. By actively engaging in this area, DH researchers can make substantial contributions and shape the trajectory of future food systems, taking into account the intricate interplay of cultural, social and ethical complexities.

Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency.

Smart meter datasets have recently transitioned from monthly intervals to one-second granularity, yielding invaluable insights for diverse metering functions. Clustering analysis, a fundamental data mining technique, is extensively applied to discern unique energy consumption patterns. However, the advent of high-resolution smart meter data brings forth formidable challenges, including non-Gaussian data distributions, unknown cluster counts, and varying feature importance within high-dimensional spaces. This article introduces an innovative learning framework integrating the expectation-maximization algorithm with the minimum message length criterion. This unified approach enables concurrent feature and model selection, finely tuned for the proposed bounded asymmetric generalized Gaussian mixture model with feature saliency. Our experiments aim to replicate an efficient smart meter data analysis scenario by incorporating three distinct feature extraction methods. We rigorously validate the clustering efficacy of our proposed algorithm against several state-of-the-art approaches, employing diverse performance metrics across synthetic and real smart meter datasets. The clusters that we identify effectively highlight variations in residential energy consumption, furnishing utility companies with actionable insights for targeted demand reduction efforts. Moreover, we demonstrate our method's robustness and real-world applicability by harnessing Concordia's High-Performance Computing infrastructure. This facilitates efficient energy pattern characterization, particularly within smart meter environments involving edge cloud computing. Finally, we emphasize that our proposed mixture model outperforms three other models in this paper's comparative study. We achieve superior performance compared to the non-bounded variant of the proposed mixture model by an average percentage improvement of 7.828%.

THU306 Association Of Prediabetes With Cardiovascular Outcomes Among Veterans With Obesity

Abstract Disclosure: J. Pendse: None. J. Mathew: None. S. Maidman: None. K. Mangalick: None. A. Ramachandran: None. E. Siddiqui: None. J.O. Aleman Diaz: None. Introduction: Prediabetes occurs frequently in obesity and is independently associated with increased atherosclerosis in nondiabetic patients. We sought to compare the effects of prediabetes on cardiovascular interventions along the glycemic control spectrum in obesity within the Veterans Health Administration (VHA), the largest US healthcare system. Methods: We conducted a systematic, retrospective review using the VHA Corporate Data Warehouse through the Veterans Administration Informatics and Computing Infrastructure database. We compared patients with obesity and prediabetes (preDM) to patients with obesity and normoglycemia (NG). Inclusion criteria included a body mass index (BMI) ≥ 30 kg/m2, Hemoglobin A1C (HbA1c) < 6.5% between 2000 and 2016. The intervention group included patients with preDM, defined by HbA1c between 5.7% to less than 6.5%, and the control group included patients with NG, defined as HbA1c< 5.7%. The primary endpoint was incidence of coronary revascularization, defined as a composite of percutaneous cardiac intervention (PCI) or coronary artery bypass graft (CABG). Secondary outcomes included PCI, CABG, diagnostic cardiac catheterizations, and mortality. Groups were compared using Pearson’s Chi-squared test or student t-tests when appropriate with alpha set to 0.05, and were assumed to have normal distribution. Results: A total of 137,487 subjects were included in the study, with 91,611 subjects with preDM and 45,876 subjects with NG. The average BMI among the preDM group was 33.8 kg/m2 ± 3.6 and the average BMI among the NG group was 33.4 kg/m2 ± 3.3 (p<0.001). Obesity/preDM subjects had a higher rate of coronary revascularization (6.3%, n=5,749) compared to obesity/NG subjects (3.1%, n=1,408) (p<0.001). From a total of 7,157 revascularized veterans, all-cause mortality rate was increased in preDM subjects (6.6%, n=851) compared to NG subjects (5.8%, n=221) (p<0.001). Obesity/preDM subjects had a higher rate of all-cause mortality (3.9%, n=3607) compared to obesity/NG subjects (2.8%, n= 1273). Also of note, obesity/preDM subjects had higher rates of diagnostic catheterization (11.9%, n=10,858), PCI (5.4%, n=4,913), stent (0.57%, n=528), CABG (1.2%, n=1087) compared with rates in obesity/NG subjects with diagnostic catheterization (7.1%, n=3272), PCI (2.6%, n=1183), stent (0.30%, n=138), and CABG (0.56%, n=258). Evaluating composite cardiovascular outcomes including PCI, stent, and CABG, obesity/preDM subjects had higher rates (6.3%, n=5749) compared with obesity/NG subjects (3.1%, n=1408). Conclusion: In this retrospective study, we have concluded that veterans diagnosed with obesity/preDM had higher rates of composite cardiovascular outcomes, including significantly higher rates of coronary revascularization procedures, overall mortality, and mortality following revascularization compared to veterans with obesity/NG. Presentation: Thursday, June 15, 2023

A Clinician's Roadmap to the Research and Data Acquisition Process Within the Veterans Health System.

Objective Identify and address potential obstacles to initiation of older population-related research within the NF/SG VHS through the provision of a concise flowchart. Setting North Florida/South Georgia Veterans Health System (NF/SG VHS). Practice Description The Department of Veterans Affairs (VA) Research Service with connection to the University of Florida facilitates research that contributes to improving the delivery of inpatient/outpatient care to veterans and their families. Practice Innovation A compendium of a senior care pharmacist's experiences will be compiled and reviewed by other specialists within the field while attempting to submit research protocols for publication within the VHS through the use of data platforms such as VINCI (VA Informatics and Computing Infrastructure) and the Corporate Data Warehouse. Main Outcome Measurements Impact of navigating research websites affiliated with and directly pertaining to the NF/SG VHS upon clinicians attempting to begin research processes within the institution. Results It was determined that for the most expeditious publication experience to result the following six steps had to be pursued sequentially: VA Institutional Review Board (IRB) Net documentation/ submission, local myIRB submission, Data Access Request Tracker/VINCI access request, setup of VINCI workspace, drafting of VINCI cohort specification, data analysis and tracking, statistical methods, abstract, and manuscript production. Conclusion This study outlines a consistent/clear method from first-hand experiences on how to navigate, more efficiently, complex research processes to produce successful future impacts on patient care.